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Manufacturing variations are becoming an unavoidable issue in modern fabrication processes; therefore, it is crucial to be able to include stochastic uncertainties in the design phase. In this paper, integrated photonic ...

Abstract The increasing penetration of photovoltaic distributed generation (PV-DG) in Radial Distribution Systems (RDSs) plays a vital role in achieving sustainable energy transition objectives; however, the inherent unc...

The application of prefabrication and modularization in the construction industry has grown significantly recently. The efficiency of prefabrication supply chains yields substantial advantages for construction projects. ...

Electrochemical potential noise signals from LiFePO4 batteries often contain a slowly varying trend component that overlaps with and distorts the intrinsic low-frequency electrochemical noise. This component must therefo...

A Self-Cooling Simulated Annealing (SCSA) algorithm is introduced for the optimization of nonlinear least-squares problems. In contrast to conventional simulated annealing techniques that require a predefined cooling sch...

An analogy with the way ant colonies function has suggested the definition of a new computational paradigm, which we call ant system (AS). We propose it as a viable new approach to stochastic combinatorial optimization. ...

Previous article Next article An Algorithm for Least-Squares Estimation of Nonlinear ParametersDonald W. MarquardtDonald W. Marquardthttps://doi.org/10.1137/0111030PDFPDF PLUSBibTexSections ToolsAdd to favoritesExport Ci...

Materie / parole chiave: multi-criteria decision making, socio-technical decision modeling, robust and stochastic optimization, human factors and ergonomics, supply chain and logistics analytics, digital twins and simulation; Technology: Technol...

The (static) traffic assignment (TA) problem, which computes network equilibrium flows from origin–destination (OD) demand under flow conservation, is central to transportation modeling. As multimodal transportation sy...

Variable selection is fundamental to high-dimensional statistical modeling, including nonparametric regression. Many approaches in use are stepwise selection procedures, which can be computationally expensive and ignore ...